herbert simon model of decision making
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A decision which cannot be made by using a rule or a model is the non-programmed decision. Such decisions are
infrequent but the stakes are usually larger. Therefore, they cannot be delegated to the lower level. The MIS in the
non-programmed decision situation can help to some extent, in identifying the problem, giving the relevant
information to handle the specific decision-making situation. The MIS, in other words, can develop support system
in the non-programmed decision-making situation. Advertising budgets, new product decisions and similar
problems illustrate the non-programmed type of decision that cannot be automated.The major reason for distinguishing these two types of decisions is to arrive at some classification of decision-
making methods in order to improve decision-making.
HERBERT SIMON MODELDecision-making is a process in which the decision-maker uses to arrive at a decision. The core of this process is
described by Herbert Simon in a model. He describes the model in three phases as shown in the figure below:I. Intelligence: raw data collected, processed and examined, Identifies a problem calling for a decision.II. Design: inventing, developing and analyzing the different decision alternatives and testing the feasibility
of implementation. Assess the value of the decision outcome.III. Choice: select one alternative as a decision, based on the selection criteria.
In the intelligence phase, the MIS collects the data. The data is scanned, examined, checked and edited. Further, the
data is sorted and merged with other data and computations are made, summarized and presented. In this
process, the attention of the manager is drawn to all problem situations by highlighting the significant differences
between the actual and the expected, the budgeted or the targeted.In the design phase, the manager develops a model of the problem situation on which he can generate and test
the different decision alternatives, he then further moves into phase of selection called as choice. In the phase of choice, the manager evolves selection criteria such as maximum profit, least cost, minimum
wastage, least time taken and highest utility. The criterion is applied to the various decision alternatives and the
one which satisfies the most is selected.In these phases, if the manager fails to reach a decision, he starts the process all over again and again. An ideal MISis supposed to make a decision for the manager.An example of the Simon model would illustrate further its use in the MIS. For example, a manager finds on
collection and through the analysis of the data that the manufacturing plant is underutilized and the products
which are being sold are not contributing to the profits as desired. The problem identified, therefore, is to find a
product mix for the plant, whereby the plant is fully utilized within the raw material and the market constraints,
and the profit is maximized. The manager having identified this as the problem of optimization, now examines the
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use of linear programming (LP) model. The model is used to evolve various decision alternatives. However,
selection is made first on the basis of feasibility and then on the basis of maximum profit.The product mix so given is examined by the management committee. It is observed that the market constraints
were not realistic in some cases and the present plant capacity can be enhanced to improve the profit. The same
model is used again to tool the revised position. Therefore, additional data is collected and an analysis is made to
find out whether the average 20 percent utilization of the capacity can be increased. A market research for someproducts is made and it is found that some constraints need to be removed and reduced. Based on the revised
data linear programming model is used and a better optimum solution is obtained.
It is necessary to understand the concept of decision-making as they are relevant to the design of the MIS. The
Simon model provides a conceptual design of the MIS and decision-making wherein the designer has to design the
system in such a way that the problem is identified in precise terms. That means the data gathered for data
analysis should be such that it provides diagnostics and also provide a path to bring the problem to surface.